Materka, MaZda — a Software for Texture Analysis, Proc. Krzemińska-Pakuła, Analysis of Intracardiac Masses in Cardiac Tumour Echocardiograms, Proc. Spis treści Selected publications Books M. Stødkilde-Jørgensen, Textures in magnetic resonance images of the ischemic rat brain treated with an anti-inflammatory agent, Clinical Imaging, 34, 1, 2010, pp. Ślot, Stereovision-based Obstacle Avoidance Procedure for Autonomous Mobile Platforms, Proc.
. This algorithm finds corner by sliding set of three rectangles along the curve and counting number of contour points lying in each rectangle. Drozdz, Tissue Identification of Intracardiac Masses in Adults Using Neural Networks, suppl. Proposed technique was found very consistent with human vision system. Materka, Texture in Biomedical Images. Ślot, Obstacle Avoidance Procedure and Lee Algorithm Based Path Replanner for Autonomous Mobile Platforms, International Journal of Electronics and Telecommunications, 59, 1, 2013, pp.
Moreover, most of the edges are removed from the visual representation which allows keeping the overview over complex graphs with dense subgraphs. Kasprzak, Application of neural networks for the analysis of histological and ultrasonic aortic wall appearance — an in-vitro tissue characterization study, Ultrasound in Medicine and Biology, 34, 1, 2008, pp. Szymajda, On the influence of the image normalization scheme on texture classification accuracy, Proc. In a crossing, the usual black road surface is painted with constant width periodic white bands. Tadeusiewicz , Warsaw University, 2010, pp.
Strzelecki, Classification of Breast Thermal Images using Artificial Neural Networks, Journal of Medical Informatics and Technologies, Dept. Kim, Implementation of a synchronized oscillator circuit for fast sensing and labeling of image objects, Sensors, 11, 4, 2011, pp. Schad, Feature Evaluation of Texture Test Objects for Magnetic Resonance Imaging, in Texture Analysis in Machine Vision, Series in Machine Percept. Lin, Automatic Detection of Pancreatic Islets in Magnetic Resonance Rat Liver Images, Proc. Drews-Peszyński, Advanced Thermal Image Processing, in Medical Devices and Systems, The Biomedical Engineering Handbook ed. This technique is very useful to detect corners from noisy shapes and natural object boundaries.
Criteria for evaluation of corner detection algorithms are proposed in this paper. Lerski , Med4 publishing, 2006, pp. Drozdz, Validation of Neural Networks for the Identification of Intracardiac Masses, 7th International Congress Polish Cardiac Society, September 11-13, 2003, Gdynia-Sopot-Gdańsk, in Kardiologia Polska, Polish Heart Journal, t. Janowski, Morphological Characteristics of Skin Mast Cells Using Image Analysis, 20-th Congress of the International Society for Skin Imaging, Wien 1997, abstract in Skin Research and Technology, vol. Sygut, Implementation Of An Image Analysis System For Morphological Characteristics Of Urticaria Pigmentosa Skin Mast Cells, Medical Science Monitor 3 2 , 1997, pp. Schad, Evaluation of Texture Features of Test Objects for Magnetic Resonance Imaging, Infotech Oulu Workshop on Texture Analysis in Machine Vision, June, Oulu, Finland, pp.
Kim, Hybrid no-propagation learning for multilayer neural networks, Neurocomputing, 321, 2018, pp. Kaszuba, Cold Provocation and Active Thermography in Medical Screening, Computational Methods in Science and Technology, 23, 1, 2017, pp. Strzelecki, Segmentation of Textured Biomedical Images using Multilayer Neural Networks, Medical Science Monitor 2 4 , 1996, pp. For each pair of images to compare, the scheme consists in evaluating specific color features adapted to this pair. Pietikainen , World Scientific, Singapore 2000, pp. Then we propose to analyze the spatial co-occurrences between the adapted features to compute the image indices. This is an efficient method, as it does not involve calculation of cosine angle and curvature.
Strzelecki, Network of Synchronised Oscillators — a Digital Approach, Proc. Materka, Parameter Estimation of Markov Random Field of Image Textures, Bulletin of the Polish Academy of Science, Technical Sciences, 4, 2, 1996, pp. Szczypinski, MaZda, in Texture analysis for Magnetic Resonance Imaging eds. Strzelecki, Image texture segmentation using oscillator networks and statistical methods, Technical University of Lodz, Lodz 2004 in Polish K. Więcek, Thermal modelling and screening method for skin pathologies using active thermography, Biocybernetics and Biomedical Engineering, 38 3 , 2018, pp. Czubiński, Nevus atypical pigment network distinction and irregular streaks detection in skin lesions images, Proc. Computational Imaging and Vision, vol 32.
The algorithm has a potential to visualize very large networks because it uses modern clustering heuristics which are optimized for large graphs. The crossing region as well as its length is determined using this concept. Lipiec, Analysis of myocardial texture in resting echocardiographic images predicts recovery one year after myocardial infarction, Proc. Strzelecki, Application of Coupled Neural Oscillators for Image Texture Segmentation and Biological Rhythms Modelling, Int. Synder, Computerized analysis of texture in bone radiograms using MaZda software, Polish Journal of Radiology, 68, 4, 2003, pp.
Abstract Visualization of large complex networks has become an indispensable part of systems biology, where organisms need to be considered as one complex system. Strzelecki, MeMoS - a software tool for extraction of anatomical structures data from 3D medical images, Proc. Strzelecki, Wavelet transform, in Biocybernetics and Biomedical Engineering 2000 ed. Experimental results using real road scenes with pedestrian crossing confirm the effectiveness of the proposed method. Strzelecki, On the Effect of Image Brightness and Contrast Nonuniformity on Statistical Texture Parameters, Foundations of Computing and Decision Sciences, 40 3 , pp.